Network Operations

5 automated security scanners

Network Detection Response

Purpose: This scanner analyzes network detection and response capabilities for a given domain by examining various indicators of potential vulnerabilities in east-west traffic monitoring, command and control (C2) detection, living-off-the-land techniques, and automated response mechanisms. It evaluates the presence of these indicators to assess the overall risk level associated with network defense readiness.

What It Detects:

East-West Monitoring: Detection of potential lateral movement through monitoring of east-west traffic for signs of unauthorized access or suspicious activities.
Lateral Movement Detection: Identification of techniques used to move laterally within a network, such as privilege escalation and kerberoasting attacks.
Segmentation Visibility: Assessment of the visibility into zero-trust segmentation policies and detection of policy violations that could lead to unauthorized access.
C2 Detection: Analysis for command and control (C2) communication channels that may indicate malicious activity or ongoing exploitation attempts.
DNS Analysis: Examination of DNS queries for tunneling activities, which can be used in C2 communications or data exfiltration.
TLS Anomaly Detection: Identification of anomalies in TLS traffic patterns that could signify potential security breaches or unauthorized access.
Living-Off-the-Land Detection: Scrutiny of common tools and techniques used by adversaries to operate within the network without leaving significant digital footprint.
Protocol Abuse: Monitoring for misuse of standard communication protocols, such as SMB, which can be abused in phishing attacks or lateral movement.
Automated Response Capabilities: Evaluation of the system’s ability to automatically respond to detected threats, including containment and mitigation strategies.
Multi-Cloud/Container Network Visibility: Analysis of cloud and container infrastructure for visibility into multi-cloud environments and potential misconfigurations that could be exploited by adversaries.

Inputs Required:

Domain Name: The target domain whose network detection capabilities are to be assessed.

Business Impact: The ability to detect and respond effectively to network threats is crucial for maintaining the integrity and security of an organization’s digital assets. Inefficient or inadequate network detection can lead to unauthorized access, data breaches, and significant financial losses due to cyber-attacks.

Risk Levels:

Critical: The domain lacks comprehensive east-west monitoring, C2 detection capabilities, automated response mechanisms, or multi-cloud/container network visibility. This severely compromises the organization’s security posture against sophisticated threats.
High: There are gaps in specific areas such as east-west monitoring, C2 detection, or automated response that significantly increase the risk of potential breaches and unauthorized access attempts.
Medium: The domain exhibits partial coverage in network defense capabilities with some deficiencies that could be exploited by adversaries but do not pose an immediate critical threat to all assets.
Low: The domain demonstrates a robust level of network detection and response, effectively mitigating most risks associated with current threats without significant capability gaps.
Info: Informal findings indicating minor deviations from best practices in network monitoring that are generally safe or require further investigation for risk assessment.

Example Findings:

A detected lateral movement activity was identified through east-west traffic analysis, which could indicate a potential security breach requiring immediate attention to secure the system and investigate unauthorized access attempts.
Inadequate DNS analysis flagged an ongoing C2 communication channel that was not previously visible in network monitoring logs, highlighting a need for enhanced visibility into command and control activities within the infrastructure.

Network Behavior Analytics

Purpose: The Network Behavior Analytics scanner is designed to assess the capabilities of a domain in detecting and managing network behavior analytics. It evaluates the presence of adaptive baselines, model management, and false positive handling mechanisms that are crucial for enhancing cybersecurity posture.

What It Detects:

The scanner identifies whether a domain has an adaptive baseline methodology or self-learning capabilities.
It checks for mention of peer comparison or role-based baseline in network architecture discussions.
It looks for mentions of model versioning, ML operations, and automated retraining mechanisms within the documentation.
It assesses the presence of concept drift detection or model drift monitoring to ensure up-to-date analytics models.
The scanner evaluates the effectiveness of false positive reduction strategies and threshold tuning capabilities in reducing alert noise.
It also detects the capability to identify slow attack patterns through time series analysis, which is critical for anticipating potential threats.
Lastly, it identifies insider threat detection mechanisms such as privileged user monitoring or UEBA analytics that help in preventing data exfiltration incidents.

Inputs Required:

domain: The target domain whose network behavior analytics capabilities need to be assessed.

Business Impact: The ability to detect and manage network behavior analytics is pivotal for maintaining a robust cybersecurity framework. Inadequate detection mechanisms can lead to missed threats, while ineffective management of false positives can result in alert fatigue, reducing the utility of security tools.

Risk Levels:

Critical: The scanner flags a critical risk when there are no adaptive baselines, model management capabilities, or effective handling of false positive alerts detected. This indicates significant gaps that could lead to severe vulnerabilities.
High: When partial capabilities such as adaptive learning or FP management are present but comprehensive NBA features are missing, the risk level is high due to potential exposure to critical threats without adequate detection and mitigation tools.
Medium: Medium risk levels arise when specific aspects of NBA are detected but other key components like slow attack detection or insider threat analytics are absent, suggesting a need for improvement in certain areas of network security.
Low: When all main features of the scanner’s purpose are adequately covered without significant gaps, the risk level is considered low, indicating a well-rounded and robust cybersecurity posture.
Info: This category includes any findings that do not directly impact critical vulnerabilities but still highlight specific areas for improvement or information about current capabilities.

Example Findings:

The domain lacks adaptive baseline methodology, which could lead to missed threats in network behavior analytics.
There are no mentions of model versioning within the documentation, indicating a lack of proactive management of analytical models.

Encrypted Traffic Analysis

Purpose: The Encrypted Traffic Analysis Scanner is designed to assess and evaluate the visibility capabilities of encrypted traffic in various environments. It aims to identify blind spots where critical threats can hide, such as certificate pinning bypasses, DNS-over-HTTPS/TLS tunneling, missing JA3/JA3S fingerprinting analysis, and inadequate monitoring of east-west encryption.

What It Detects:

TLS/SSL Inspection Implementation: The scanner tests for the presence of man-in-the-middle proxy deployment, enterprise CA certificate distribution, enforcement of decryption policies, detection of inspection bypass methods, and flags uninspected traffic categories.
Certificate Pinning Handling: It evaluates pinning detection mechanisms, checks for pinned application inventory, verifies capabilities to bypass or inspect despite pinning, detects unmanaged pinned applications, and highlights gaps in inspection due to pinning.
Encrypted DNS Visibility: The scanner tests for the detection of DoH/DoT traffic, encrypted DNS proxy/blocking, restoration of DNS query visibility, and flags any tunneling over HTTPS that eludes monitoring.
TLS Fingerprinting Deployment: It assesses the collection of JA3/JA3S fingerprints, identifies malware family characteristics, verifies threat intelligence from fingerprints, detects missing analysis for fingerprinting, and flags gaps in identification capabilities.
East-West Encryption Monitoring: The scanner tests for internal TLS inspection, visibility into lateral movement, enforcement of micro-segmentation encryption policies, detects any blind spots in internal encryption monitoring, and identifies coverage gaps in monitoring.

Inputs Required:

domain (string): A fully qualified domain name (e.g., acme.com) is required as input to perform the analysis on specific targets.

Business Impact: The ability to detect encrypted traffic blind spots is crucial for security operations, as these blind spots can enable critical threats such as malware lateral movement and data exfiltration through unmonitored channels. Effective visibility into encrypted traffic helps in mitigating risks associated with unauthorized access and data breaches.

Risk Levels:

Critical: The scanner identifies a significant gap where threats can hide without effective TLS inspection, certificate pinning handling, DNS over HTTPS/TLS visibility, JA3/JA3S fingerprinting deployment, or east-west encryption monitoring.
High: The scanner detects partial visibility in at least one of the aforementioned areas (e.g., missing DoH detection or incomplete TLS fingerprinting).
Medium: The scanner identifies potential risks where improvements could enhance security posture but does not currently indicate a significant vulnerability.
Low: The scanner confirms adequate coverage across all aspects of encrypted traffic visibility, with minimal identified issues.
Info: Informal findings that do not directly impact the risk level but may suggest areas for improvement or verification.

Example Findings:

“Critical encrypted traffic visibility gap: no inspection, DNS control, or fingerprinting detected.”
“Partial visibility: DoH/DoT control present but missing inspection/fingerprinting.”

This structure provides a detailed overview of the scanner’s purpose and capabilities, along with clear descriptions of its inputs, business impact, risk levels, and example findings based on typical scenarios it might encounter during operation.

Network Forensics Capability

Purpose: This scanner evaluates network forensics capabilities by analyzing a domain for disclosures related to packet capture, sampling policies, retention durations, storage architectures, reconstruction capabilities, and retrospective analysis. It aims to identify gaps in forensic capabilities that could affect legal admissibility and security posture.

What It Detects:

Packet Capture Disclosure: Identifies if the domain discloses any form of packet capture capability.
Sampling Policy Detection: Alerts for any detected sampling policies, which may indicate incomplete capture.
Capture Completeness: Detects disclosures related to zero packet loss and guaranteed capture.
Retention Duration: Uncovers any disclosed retention durations or storage architectures that could affect evidence preservation.
Reconstruction Capabilities: Identifies if the domain has capabilities for network data reconstruction.
File Extraction: Detects file carving and malware extraction capabilities, which are indicative of broader forensic capabilities.
Retrospective Analysis: Uncovers any disclosures related to retrospective analysis that could enhance investigative capabilities.
Metadata Indexing: Identifies if metadata indexing is present, which may suggest search and retrieval enhancements.
Chain of Custody: Detects chain of custody controls that are crucial for legal admissibility.
Evidence Integrity: Alerts for cryptographic hashes or other integrity checks that could enhance evidence authenticity.
Legal Compliance: Identifies if the domain complies with legal requirements related to forensic evidence.

Inputs Required:

domain: The target domain whose network forensics capabilities are to be assessed.

Business Impact: This assessment is critical as it directly impacts an organization’s ability to preserve and present digital evidence in a legally admissible format. Inadequate forensic capabilities can lead to significant risks, including loss of crucial evidence and potential legal repercussions.

Risk Levels:

Critical: The scanner flags severe gaps where no packet capture, retention policies, or reconstruction capabilities are disclosed. This is highly critical as it significantly impacts the organization’s ability to conduct effective digital forensics.
High: The domain discloses partial forensic details such as incomplete capture or limited reconstruction capabilities. This poses a significant risk as it may lead to insufficient evidence preservation and potential legal issues.
Medium: There are subtle gaps in forensic practices, such as missing retention policies or incomplete analysis procedures. While less severe than critical, this still represents a notable deficiency that warrants attention.
Low: The domain exhibits robust forensic capabilities including full packet capture, adequate retention, and comprehensive reconstruction processes. This is considered low risk but should not be overlooked for continuous improvement.
Info: Informal findings such as minor sampling policies or minimal legal compliance disclosures are flagged as informational since they do not significantly impact the organization’s security posture.

Example Findings:

The domain discloses only a partial packet capture method, which may lead to incomplete evidence collection and potential legal issues.
No retention policy is disclosed, posing a risk of losing critical digital evidence over time.

Network Automation Security

Purpose: The Network Automation Security Scanner is designed to assess and identify vulnerabilities in network automation systems that could lead to unauthorized access or data leakage. It focuses on testing for hardcoded credentials, unauthenticated API interactions, insecure CI/CD practices, inadequate configuration validation, and lack of automated rollback mechanisms.

What It Detects:

Credential Management in Automation: This includes the integration with secrets management solutions, detection of hardcoded credential patterns, verification of vault or secrets manager usage, and identification of plaintext credentials within repositories.
Network Device API Security: The scanner checks for authentication requirements on network device APIs, identifies default credentials, verifies certificate-based authentication methods, detects interfaces that do not require authentication, and flags any gaps in API security controls.
CI/CD Pipeline Security: It evaluates pipeline access controls, deployment approval gates, artifact signing or validation processes, and the absence of direct production environment access to detect potential security risks within CI/CD pipelines.
Configuration Validation: This involves testing for pre-deployment tests that validate configurations, syntax checking, enforcement of security policies, and the presence of automated testing stages to ensure configuration integrity.
Emergency Rollback Capability: The scanner assesses the availability of automated rollback mechanisms, configuration versioning, state management, and any limitations in emergency recovery processes.

Inputs Required:

domain (string): Fully qualified domain name (e.g., acme.com) - This is essential for making network requests to analyze automation security practices within the specified domain.

Business Impact: Network automation plays a critical role in modern IT infrastructure, and its vulnerabilities can lead to significant risks such as unauthorized access to sensitive data, system compromise, and extended outage durations due to manual intervention only. The scanner helps organizations proactively identify and mitigate these risks to ensure robust security practices within their network automation environments.

Risk Levels:

Critical: This severity level is triggered when there are no vault integrations, API authentication mechanisms, or comprehensive pipeline security detected across all tested domains.
High: Triggered when partial security measures such as vault integration and API authentication are present but critical elements like pipeline security are missing.
Medium: Indicates a situation where only individual security measures (like vault integration) are found without the need for broader assessment of other potential gaps in automation security.
Low: Assigned when all necessary security checks yield positive results, indicating minimal risk or no detected vulnerabilities that would compromise network integrity.
Info: Used for informational findings that do not directly impact system security but may indicate areas for improvement or further investigation.

If the README doesn’t specify exact risk levels, infer them based on the scanner’s purpose and impact:

Example Findings:

A critical vulnerability was detected in the configuration validation process where pre-deployment tests were found to be insufficiently robust, potentially leading to unauthorized data access.
The absence of automated rollback mechanisms during CI/CD pipeline testing highlighted a significant security gap that could lead to prolonged system unavailability and potential data loss due to human error or delay in intervention.